| language: en | |
| license: mit | |
| library_name: timm | |
| tags: | |
| - image-classification | |
| - resnet50 | |
| - cifar10 | |
| datasets: cifar10 | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: resnet50_supcon_cifar10 | |
| results: | |
| - task: | |
| type: image-classification | |
| dataset: | |
| name: CIFAR-10 | |
| type: cifar10 | |
| metrics: | |
| - type: accuracy | |
| value: 0.9518000000000001 | |
| # Model Card for resnet50_supcon_cifar10 | |
| This model is a small resnet50 trained on cifar10. | |
| - **Test Accuracy:** 0.9518000000000001 | |
| - **License:** MIT | |
| ## How to Get Started with the Model | |
| Use the code below to get started with the model. | |
| ```python | |
| import detectors | |
| import timm | |
| model = timm.create_model("resnet50_supcon_cifar10", pretrained=True) | |
| ``` | |
| ## Training Data | |
| Training data is cifar10. | |
| ## Training Hyperparameters | |
| - **config**: `None` | |
| - **model**: `resnet50_supcon_cifar10` | |
| - **batch_size**: `512` | |
| - **epochs**: `501` | |
| - **lr**: `0.5` | |
| - **warmup_epochs**: `10` | |
| - **validation_frequency**: `50` | |
| - **output_features_dim**: `128` | |
| - **seed**: `1` | |
| - **debug**: `False` | |
| - **dataset**: `cifar10` | |
| - **training_mode**: `supcon` | |
| ## Testing Data | |
| Testing data is cifar10. | |
| --- | |
| This model card was created by Eduardo Dadalto. |